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Lobsters

by io.github.pipeworx-io

Polymarket–Kalshi Spread

polymarket_kalshi_spread
Read-onlyIdempotent

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) topic — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit kalshi_event_ticker + polymarket_event_slug for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoPre-mapped: fed | btc | cpi | gdp | sp500 | recession | next_pope | next_uk_pm | next_israel_pm | 2028_president
kalshi_event_tickerNoExplicit Kalshi event ticker, e.g. "KXFED-26OCT". Overrides the topic-mapped Kalshi side.
polymarket_event_slugNoExplicit Polymarket event slug, e.g. "fed-decision-in-june-825". Overrides the topic-mapped Polymarket side.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "topic": "fed"
+  },
+  {
+    "topic": "btc"
+  }
+]
  2. Added

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Even though annotations already mark the tool as read-only, idempotent, and non-destructive, the description adds deep behavioral detail: the token-overlap matching algorithm, pairing_unverified set in either mode, unknown metric_type legs never paired, gross (not net) spreads due to unmodeled Kalshi fees, and the precise null semantics of temporal_alignment. This is exceptional disclosure beyond anything annotations or schemas provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every sentence earns its place and it is carefully structured with labeled blocks (TWO MODES, RESPONSE, SAFETY FIELDS, codes, skipped counters). The purpose sentence is front-loaded, and the dense caveats are scannable and purposeful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully carries the burden of explaining return values and does so thoroughly: leg-by-leg prices, top_spreads_pp, compatibility fields, temporal_alignment null semantics, fees_note, and skipped_cross counters. It also warns against over-trusting macro shortcuts, covering both functional and interpretive needs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters, so the baseline is 3. The description adds mode semantics — how explicit kalshi_event_ticker and polymarket_event_slug override the topic-mapped side — and lists all ten topic shortcuts, which meaningfully enriches the bare schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific function — cross-venue spread between Kalshi and Polymarket for the same resolving question — with a clear verb and resource. It does not explicitly name sibling tools like polymarket_arbitrage to differentiate, but the scope is unambiguous and the title reinforces the focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly describes two invocation modes (topic shortcuts vs explicit kalshi_event_ticker + polymarket_event_slug) and when each is appropriate, and warns that most pre-mapped topics return compatibility warnings today. However, it does not explicitly contrast with sibling tools, so no explicit alternatives or exclusions are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., three tools for querying Pipeworx data (ask_pipeworx, ask_pipeworx_grounded, deep_research), and six tools for Polymarket prediction markets. The boundaries between them are unclear, causing potential for misselection.

Naming Consistency3/5

Tool names are all snake_case but follow inconsistent patterns: some use verb_noun (get_hottest, get_newest), some are single verbs (remember, forget), and others are noun_noun (bet_research, polymarket_arbitrage). While readable, the lack of a consistent pattern adds confusion.

Tool Count2/5

With 34 tools, the server is overloaded, especially given its name 'Lobsters' suggests a focus on that site, yet only 4 tools are Lobsters-related. The majority belong to Pipeworx, Polymarket, and generic utilities, making the scope extremely broad and unfocused.

Completeness2/5

For the implied domain of Lobsters, the tool set is incomplete (missing create/update/delete). For the broader domains (Pipeworx, Polymarket), the set is extensive but doesn't align with the server's name. The lack of a coherent domain leaves obvious gaps relative to any single purpose.

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